# Announcing another slopegraph plotting function -- June 14, 2018

Tagged as: [R

ggplot2

functions

dplyr

slopegraph

CRAN

*]*ggrepel

A couple of weeks ago I wrote a blog post about slopegraphs. There was some polite interest and it was a good chance to practice my functional programming skills so I decided to see if I could make a decent R function from what I had learned. It’s in pretty good shape so I just pushed an update to CRAN (it will take awhile to process). You can also get the latest version from GitHub.

The documentation for it is here. Longer term I hope to move it here.

## Overview

The package also includes other functions that I find useful for teaching statistics as well as actually practicing the art. They typically are not “new” methods but rather wrappers around either base R or other packages and concepts I’m trying to master.

`Plot2WayANOVA`

which as the name implies conducts a 2 way ANOVA and plots the results using`ggplot2`

`PlotXTabs`

which as the name implies plots cross tabulated variables using`ggplot2`

`neweta`

which is a helper function that appends the results of a Type II eta squared calculation onto a classic ANOVA table`Mode`

which finds the modal value in a vector of data`SeeDist`

which wraps around ggplot2 to provide visualizations of univariate data.`OurConf`

is a simulation function that helps you learn about confidence intervals

## Installation

```
# Install from CRAN
install.packages("CGPfunctions")
# Or the development version from GitHub
# install.packages("devtools")
devtools::install_github("ibecav/CGPfunctions")
```

## Credits

Many thanks to Dani Navarro and the book > (Learning Statistics with
R)
whose etaSquared function was the genesis of `neweta`

.

“He who gives up safety for speed deserves neither.” (via)

#### A shoutout to some other packages I find essential.

- stringr, for strings.
- lubridate, for date/times.
- forcats, for factors.
- haven, for SPSS, SAS and Stata files.
- readxl, for
`.xls`

and`.xlsx`

files. - modelr, for modelling within a pipeline
- broom, for turning models into tidy data
- ggplot2, for data visualisation.
- dplyr, for data manipulation.
- tidyr, for data tidying.
- readr, for data import.
- purrr, for functional programming.
- tibble, for tibbles, a modern re-imagining of data frames.

## Leaving Feedback

If you like **CGPfunctions**, please consider leaving feedback
here.

## Contributing

Contributions in the form of feedback, comments, code, and bug reports are most welcome. How to contribute:

- Issues, bug reports, and wish lists: File a GitHub issue.
- Contact the maintainer ibecav at gmail.com by email.